PROJECT SUMMARY/ABSTRACT Antibiotics use has reached enormous proportions around the world. A well-known consequence of antibiotic use is the development of bacterial antibiotic resistance. The impact of antibiotics on host and microbial function, on the other hand, has not been well recognized until recently. The intestinal microbiota aids the host in metabolic and immunological development and provides beneficial functions such as vitamin production and pathogen displacement. Dysbiosis of gut microbiota is not only associated with higher risk to pathogenic microbes, but linked to a large number of complex diseases such as cancers and brain disorders. Despite of the rapid progresses being made, significant challenges still arise in the study of complex microbiomes, essentially stemming from the presence of highly similar bacterial species and strains with complex genomes. A fundamental limitation of all existing metagenomics methods, represented by the widely used 16S rRNA sequencing and whole metagenome shotgun sequencing, is that they provides insufficient discriminative power to distinguish among closely related species and strains with high sequence similarity, or confidently map mobile genetic elements (such as plasmids) to their host genomes. This limitation often leads to fragmented pictures (large number of short contigs) at a limited resolution that prevents an in-depth characterization of the effect of antibiotics on gut microbiome. In this project, we will build on a highly innovative method we recently prototyped for high resolution metagenomic analysis based on long-read Single Molecule Real Time (SMRT) sequencing, and apply the novel methods to perform in-depth characterization of metagenomic changes and transmission of mobile genetic elements in response to different types of antibiotics. We expect this study to uncover novel biological insights, undetectable by previous methods, into the complex genomic dynamics of microbiomes in response to antibiotics, and provide a novel and general method to help high resolution characterization of microbiomes. !